JAQM Volume 9, Issue 4 - December 30, 2014

Contents

The Stochastic Frontier Analysis permits evaluating the Technical Efficiency scores for one output variable to obtain the corresponding Technical Efficiency of n Decision-Making Units (DMU). The objective of this work is a comparison between a Stochastic Frontier Analysis, with same input and different output variables, and the Data Envelopment Analysis. You get k Technical Efficiency TE(yi) which are unified by a Principal Component Analysis and compared with the results of a DEA on the same data.

Missing data (MD) are a common problem in medical research. When ignored or treated not appropriately, MD can lead to seriously biased results. Currently, there are no comprehensive guidelines for efficiently identifying suitable imputation methods in different MD situations. The objective of the paper is to discuss various methods to handle missing data. Based on a selective literature search, common MD imputation methods were identified. A decision algorithm is presented where the considered methods are prioritized with respect to the underlying missing data mechanism and scale level of the incomplete data. Furthermore, all included imputation methods are described in more detail. No alternative decision algorithms for MD imputation methods of this complexity have been developed yet, wherefore it could serve as a useful tool for researchers confronted with MD.

The FDI have become a very important aspect in the nowadays economical and geopolitical circumstances and therefore the study of this phenomenon is regarded with an increased attention by scholars by government and business representatives. Following this direction the study of disparities registered between different regions or between different countries when dealing with the attractiveness of these entities in the eyes of foreign investors became a topic of an increasing importance. In the present study, using yearly data regarding the stocks of FDI at the level of the Romanian counties, for the period 2001 – 2012, I try to evaluate the evolution of the attractiveness of these entities for foreign investors using the Gini coefficient. The study reveals that the attractiveness of the Romanian counties was significantly influenced by the main events which happened during this period.

As an important tool in risk management, Value-at-Risk is estimated on the Romanian stock market based on single assets and a weighted portfolio of them. Because this is a measure of the extreme tails, several approaches are used to compute Value-at-Risk by taking in consideration the distribution of the data, namely the generalized hyperbolic distribution, Normal-Inverse Gaussian and asymmetric t-Student in comparison with the normal distribution. The considered period is divided into an analyze period and a test one, where based on the rolling windows approach are estimated the VaR values and then tested with the help of Kupiec’s and Christoffersen’s backtests. The choice of the time period affects the estimation due to the events that took place on the market and the approach based on the normal distribution predicted best the VaR values by underestimating the risk compared to the other distributions. This approach fits better the considered period because the analyzed period covers moments of severe economical crisis while the test period goes over a period of recovery.

The knowledge-based economy places great importance on the diffusion and use of information and knowledge as well as its creation. The determinants of success of enterprises, and of national economies as a whole, is ever more reliant upon their effectiveness in gathering and utilizing knowledge. This paper is based on 2 different surveys, 4 years apart, on Romanian companies, addressing perception of knowledge based economy by local CEOs or entrepreneurs. It emphasize the changes in perception of this topic and the trends in this matter.

The present paper approaches the issue of identifying the most suitable position of a distribution point in order to make it attractive and accessible to most “power centers” (sources of potential buyers, donors, etc.), starting from the gravitational model used in Physics. Our study took into account Railly’s formula into which an additional variable was introduced, namely, the land price in the area at a certain distance from the power centers. The results present deviations from the calculated distances according to Railly’s formula, in the sense that they get closer to the minimum price area.